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The data are limited to inpatient mortality and there is not assumption that the mortality trend persists beyond the inpatient setting.
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While parsimony is sometimes justified as model-free, it has mathematical properties and is not assumption-free; therefore explicit models should be generated for many biological problems.
External spike-in controls are not assumption-free; it is assumed that the experimenter starts with the same quantity of equal quality template.
However, that doesn't mean that there aren't assumptions and stereotypes that limit how we might approach negotiating a deal.
Of course, the Bayesian paradigm is not without assumptions and limitations.
We now present two examples where Assumption 2.2 is not satisfied, but Assumption 2.1(2) is satisfied.
However, one could argue that although the same-property interpretation makes this assumption, it is not an unjustified assumption.
That was a reasonable assumption then, but it is not a reasonable assumption now.
It is not a bad assumption, as far as assumptions go.
If the planar assumption is not fulfilled, the uniform coordinate assumption is not fulfilled either.
It is not a flattering assumption.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com